A Novel High-Throughput Acceleration Engine for Read Alignment

Abstract

The Smith-Waterman (S-W) algorithm is widely adopted by the state-of-the-art DNA sequence aligners. Existing wave front-based methods ignored the fact that the S-W algorithm is fed with significantly varied-size inputs in modern aligners, in which the S-W algorithm is further optimized by exerting extensive pruning. In this paper, we propose an architecture, tailored for varied input sizes as well as harnessing software pruning strategies, to accelerate S-W. Our implementation demonstrates a 26.4x speedup over a 24-thread Intel Has well Xeon server, and outperforms wave front-based implementations by up to 6x with the same FPGA resource.